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20172024
most citedImproving Stock Market Prediction via Heterogeneous Information Fusion

210 citations · 281 across the 5 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2024★ 1 cited

A Differential Geometric View and Explainability of GNN on Evolving Graphs

Yazheng Liu, Xi Zhang, Sihong Xie

Graphs are ubiquitous in social networks and biochemistry, where Graph Neural Networks (GNN) are the state-of-the-art models for prediction. Graphs can be evolving and it is vital…

cs.LG2022

Provable Robust Saliency-based Explanations

Chao Chen, Chenghua Guo, Rufeng Chen +5

To foster trust in machine learning models, explanations must be faithful and stable for consistent insights. Existing relevant works rely on the distance for stability as…

cs.LG2022★ 2 cited

Are Your Reviewers Being Treated Equally? Discovering Subgroup Structures to Improve Fairness in Spam Detection

Jiaxin Liu, Yuefei Lyu, Xi Zhang +1

User-generated reviews of products are vital assets of online commerce, such as Amazon and Yelp, while fake reviews are prevalent to mislead customers. GNN is the state-of-the-art…

cs.LG2021

Multi-objective Explanations of GNN Predictions

Yifei Liu, Chao Chen, Yazheng Liu +2

Graph Neural Network (GNN) has achieved state-of-the-art performance in various high-stake prediction tasks, but multiple layers of aggregations on graphs with irregular structures…

cs.LG2018

A Tensor-Based Sub-Mode Coordinate Algorithm for Stock Prediction

Jieyun Huang, Yunjia Zhang, Jialai Zhang +1

The investment on the stock market is prone to be affected by the Internet. For the purpose of improving the prediction accuracy, we propose a multi-task stock prediction model tha…